A Fortune 500 Bank's 9-Month Oracle Migration? We Delivered in 8 Weeks — With Zero Data Loss Across 2.1 Billion Rows.
Industry
Financial Services
Service
Data Migration & Cloud Modernization
Duration
8 weeks
Team
Agilityx consultants + AI agents
Data Volume
2.1 billion rows
The Situation
A global Fortune 500 bank was constrained by legacy Oracle systems that had become the primary bottleneck for their digital transformation. High annual licensing costs and rigid on-premise infrastructure meant that hardware was at near-maximum capacity, causing daily reporting jobs to fail and creating massive decision latency.
New analytics requests frequently took months to fulfill. The bank's internal IT department estimated that a complete migration to the Snowflake Data Cloud would require a 9-month manual effort, involving the painstaking rewrite of thousands of stored procedures and the re-mapping of complex financial schemas.
Previous attempts to modernize had been abandoned due to the risk of data loss and the inability to maintain 100% reconciliation in a highly regulated environment. With over 2.1 billion rows of transaction data at stake, the Chief Data Officer needed an 'AI-augmented' approach that could guarantee accuracy while bypassing the traditional 9-month roadmap to meet a board mandate for cost reduction.
The Approach
Discovery(Phase 1)
AI Agents
Automatically profiled 1,200+ complex table dependencies and metadata in 48 hours.
Consultants
Prioritized business-critical schemas and identified regulatory compliance guardrails.
Architecture(Phase 2)
AI Agents
Generated target-state Snowflake blueprints and security role mappings programmatically.
Consultants
Co-designed a scalable cloud-native data model aligned with Snowflake best practices.
Migration(Phase 3)
AI Agents
Executed automated SQL conversion and generated optimized Snowflake ETL/ELT code.
Consultants
Resolved complex edge-case stored procedures and handled high-risk financial logic.
Validation(Phase 4)
AI Agents
Performed automated row-by-row reconciliation across 2.1B rows to verify full row-level reconciliation integrity.
Consultants
Led compliance audits and secured stakeholder sign-off on the migration accuracy.
Enablement(Phase 5)
AI Agents
Auto-generated comprehensive runbooks and technical documentation for the new cloud environment.
Consultants
Conducted 'Build-With' training to upskill legacy DBAs into modern Cloud Data Operators.
Traditional vs. Agilityx
| Dimension | Traditional | Agilityx |
|---|---|---|
| Schema Profiling | 6–8 weeks manual analysis | 48 hours via AI agents |
| Code Generation | 5 months manual rewrite | 3 weeks (AI-augmented) |
| Data Validation | Manual sampling (high risk) | Full row-level automated reconciliation with audit validation |
| Infrastructure Cost | High legacy overhead | 65% reduction via Snowflake |
| Total Timeline | 9 Months | 8 Weeks |
Schema Profiling
Traditional
6–8 weeks manual analysis
Agilityx
48 hours via AI agents
Code Generation
Traditional
5 months manual rewrite
Agilityx
3 weeks (AI-augmented)
Data Validation
Traditional
Manual sampling (high risk)
Agilityx
Full row-level automated reconciliation with audit validation
Infrastructure Cost
Traditional
High legacy overhead
Agilityx
65% reduction via Snowflake
Total Timeline
Traditional
9 Months
Agilityx
8 Weeks
The Outcomes
2.1B rows
Migrated
Achieved full row-level reconciliation with a controlled cutover window and no critical reporting disruptions.
65%
Cost Savings
Eliminated legacy licensing and optimized compute via Snowflake auto-scaling.
8 weeks
Accelerated Value
Delivered a '9-month project' in just 8 weeks, unblocking AI initiatives.
Self-Sufficient
Internal Capability
The bank's team now independently manages the platform using the 'Build-With' model.
"Agilityx's AI agents profiled our systems in hours, work that took our last partner 6 weeks. For the first time, our leadership is looking at the same numbers and trusting them. That's transformational for a global bank."
Chief Data Officer
Fortune 500 Financial Institution
Facing a similar challenge? Let's talk.
Book a 30-minute discovery call and let's discuss how the Build With model can work for your organization.